Abstract
Enterprise Architectures (EA) consist of a multitude of architecture elements, which relate in manifold ways to each other. As the change of a single element hence impacts various other elements, mechanisms for architecture analysis are important to stakeholders. The high number of relationships aggravates architecture analysis and makes it a complex yet important task. In practice EAs are often analyzed using visualizations. This article contributes to the field of visual analytics in enterprise architecture management (EAM) by reviewing how state-of-the-art software platforms in EAM support stakeholders with respect to providing and visualizing the “right” information for decision-making tasks. We investigate the collaborative decision-making process in an experiment with master students using professional EAM tools by developing a research study. We evaluate the students’ findings by comparing them with the experience of an enterprise architect.
Highlights
Enterprises are complex and integrated systems of processes, organizational units, resources and technologies with a multitude of relations and interdependencies
This article contributes to the field of visual analytics in enterprise architecture management (EAM) by reviewing how state-of-the-art software platforms in EAM support stakeholders with respect to providing and visualizing the “right” information for decisionmaking tasks
The main contributions of the paper are (1) the set-up for the research study, including tasks to be performed and an exemplary Enterprise Architectures (EA) designed as study object, (2) experiences in executing the study with master students, and (3) the actual study results, i.e., to what extent visual analytics is currently supported by EAM tools
Summary
Enterprises are complex and integrated systems of processes, organizational units, resources and technologies with a multitude of relations and interdependencies. We review how the tools help to provide stakeholders with the “right” information and visualize it in a suitable way. This aligns with the definition of Thomas et al, who describe visual analytics as “the science of analytical reasoning facilitated by interactive visual interfaces” [5]. The main contributions of the paper are (1) the set-up for the research study, including tasks to be performed and an exemplary EA designed as study object, (2) experiences in executing the study with master students, and (3) the actual study results, i.e., to what extent visual analytics is currently supported by EAM tools.
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